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Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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Argonne’s Leadership Computing Facility (ALCF) and Mathematics and Computer Science Division (MCS) is looking for a Postdoctoral appointee working at the intersection of scientific machine learning SciML and large-scale simulation codes.
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On any given day, you might:Evaluate open-source and internally-developed modeling and analytics tools using real business dataIntegrate internal data with external data sources and APIs to discover and implement actionable insightsDesign and craft data science models to communicate solutions to customers and company leadership We'd love to find someone who is.
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Remain current on open-source, industry, academia, and US Government techniques and tools for geospatial data science, modeling, analysis, visualization, and engineering. Familiarity with advanced geospatial data science, modeling, and analysis techniques and methods (e.g., supervised and unsupervised machine learning, GeoAI, Geosimulation, patiotemporal graphs) is a plus.
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MUST HAVE Master’s in Computer Science, Computer Engineering or related Engineering, Machine Learning, or related field; 3 yrs relevant experience in one of the following: Machine Learning, Natural Language processing, or Ontology Engineering technologies; and required skills.
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Anatomical Kinesiology Advanced Strength and Conditioning Applied Exercise Physiology Exercise and Sport Psychology Exercise Physiology Medical Terminology for Kinesiology Majors Exercise Testing and Prescription Motor Learning Introduction Biomechanics Physiological Application of Nutrition to Exercise and Physical Activity.
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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Do you have a passion for invention and self-challenge? Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USABASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C.
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The Data Science team leads the strategy, development and integration of Machine Learning and Artificial Intelligence. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
$140,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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If you're interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey! Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise.
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Master's Degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline preferred. Bachelor's Degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline required.
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machine learning open source applied science short term competitive pay jobs
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